Research on the Remaining Useful Life Prediction Algorithm for Aero-Engines Based on Transformer–KAN–BiLSTM

Predicting the remaining useful life (RUL) of aircraft engines is crucial for ensuring flight safety, optimizing maintenance, and reducing operational costs. This paper introduces a novel hybrid deep learning model, Transformer–KAN–BiLSTM, for aero-engine RUL prediction. The model is designed to lev...

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Bibliografski detalji

Glavni autori:	Kejie Xu, Yingqing Guo, Qifan Zhou
Format:	Artigo
Jezik:	Inglês
Izdano:	MDPI AG 2025-11-01
Serija:	Aerospace
Teme:	remaining useful life prediction Transformer–KAN–BiLSTM algorithms aero-engine multimodal algorithm fusion advanced predictive algorithms
Online pristup:	https://www.mdpi.com/2226-4310/12/11/998
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